Plenary Talk 4 : Learning Analytics – A Multiple Perspectives Analysis of Student Data

Summary form only given, as follows. The complete presentation was not made available for publication as part of the conference proceedings. Learning analytics (LA) is a growing research area, which aims at selecting, analyzing and reporting student data (in their interaction with the online learning environment), finding patterns in student behavior, displaying relevant information in suggestive formats; the end goal is the prediction of student performance, the optimization of the educational platform and the implementation of personalized interventions. The topic is highly interdisciplinary, including machine learning techniques, educational data mining, statistical analysis, social network analysis, natural language processing, but also knowledge from learning sciences, pedagogy and sociology. Despite its increasing popularity, LA has been applied less in the context of social media-based environments. In this talk we focus especially on research in social learning analytics area. Four research directions are tackled: analytics dashboards, predictive analytics, social network analytics and discourse analytics. We thus address the “trinity” of methodological approaches to get a more comprehensive learning analytics perspective